ABOUT DATA SCIENCE PROGRAM

Many Corporations have dramatically increased investments in their "digital enterprises" in the past few years. It has been estimated that by 2020, IT departments will be monitoring 50 times more data than they are today. This tidal wave of data is driving unprecedented demand for those with the skills required to manage and leverage these very large data sets into a competitive advantage.

These professionals are skilled in automating methods of collecting and analyzing data and utilizing inquisitive exploring techniques to discover previously hidden insight from this data that can profoundly impact the success of any business.

WHY DATA SCIENCE AT EDUPRISTINE?

Academically Rigorous: EduPristine is known for classroom training and project-based learning. This training is no exception. The program is designed and delivered by the experienced faculty and data science professionals who teach at the EduPristine campus

ELIGIBILITY

Individuals with a bachelor's degree in engineering, science, maths/statistics, finance, computer science, accounting or marketing who are intrigued by statistical and analytical practices may excel in this field

Basic Statistics methods used in business performance measures

Strong interest in data science

Hands-on experience on Core Java & Unix

Good analytical skills to grasp and apply the concepts in Hadoop

TOPICS

Module I - Big Data & Hadoop (60Hrs Classroom Training)

Introduction to Unix & PYTHON

Introduction to JAVA

Introduction to HDFS & SQOOP

Map-Reduce and its assignment

SPARK + Python & Case Study (LOG ANALYSIS)

HIVE

PIG

Oozie

Project I [Retail DOMAIN] Using all above tools

HBASE

Live Project II

Module II- Big Data TRENDS

FLUME & IMPALA + Spark Streaming

R Integration with Hadoop

Cassandra

Cloudera CCA-175 Certification Guidance (Online)

Guidance session on Job roles, Resume preparation/modification

Module III - Business Analytics (50Hrs Classroom Session)

Introduction and Data Analytics

Linear Regression

Logistic Regression

Decision Tree and Clustering

Time Series Modeling

Logistic Regression

Market Basket Analysis

Module IV - Case studies (20Hrs Classroom Session)

Cross Sell Model

Market Mix Modeling

Churn Analytics

Buy Till You Die Model

Customer Lifetime Value Analysis

Telecom Model to Estimate Bill

Module V - Data Visualization (20Hrs Classroom Session)

Introduction

The visualization design methodology

The Data Visualization Process

Working with Single Data Sources

Using Multiple Data Source

Using Calculations in Tableau

Comparing Measures Against a Goal

Tableau Geo coding,Advanced Mapping

Showing Distributions of Data

Statistics and Forecasting

Dashboard Best Practices

Sharing Your Work

Case Study

Exam/Exam Prepration

COURSE HIGHLIGHTS

Classroom Training

Get trained by topic experts with interactive learning in small batches.

Online Live Instructor base training

Learn Concepts once again though Live Online sessions.

Exam Preparation Session

Prepare rigorously before global certification exam.

Online Materials

This course serves as an introduction to the interdisciplinary and emerging field of data science. Students will learn to combine tools and techniques from statistics, computer science, data visualization and the social sciences to solve problems using data

Online Content

Certificate

A reference to get ahead in your career. At the end of the course, you will receive a Certificate of Completion.
Preparing for Data visulization global Certification
The Registration fees of 250$ to be paid by participant at the time of exam.

FAQs

Data science is the study of the generalizable extraction of knowledge from data, yet the key word is science. It incorporates varying elements and builds on techniques and theories from many fields, including signal processing, mathematics, probability models, machine learning, statistical learning, computer programming, data engineering, pattern recognition and learning, visualization, uncertainty modeling, data warehousing, and high performance computing with the goal of extracting meaning from data and creating data products.

Data Science is not restricted to only big data, although the fact that data is scaling up makes big data an important aspect of data science.

Data scientists solve complex data problems through employing deep expertise in some scientific discipline. It is generally expected that data scientists are able to work with various elements of mathematics, statistics and computer science, although expertise in these subjects are not required. This course is part of both the developer learning path and the data analyst learning path.

The study warns there is a significant shortage of qualified workers to analyze Big data sets adequately. According to the report, a shortfall of about 140,000 to 190,000 individuals with analytical expertise is projected by 2018. The study also predicts a need for an additional 1.5 million managers and analysts by that same date to fully engage the true potential of the currently available data..

Data scientists are an integral part of competitive intelligence, a newly emerging field that encompasses a number of activities, such as data mining and analysis, that can help businesses gain a competitive edge. Ken Garrison, CEO of the industry group Strategic and Competitive Intelligence Professionals (SCIP), explains, "The field involves collecting data, analyzing it and delivering the data as intelligence that is actionable."

Every domain employers in analytics required: for example- 1. Large IT companies who have an Analytics practice; 2. Analytics KPOs; 3. In-House Analytics Units of large corporate; and 4. Analytics firms.

It's an Online class which will cover any new updates or topics in Big data field. We keep this as an initiative for all old students to update on new techniques in the market. There will be a 3Hrs online interactive session on every 2nd & 4th Sunday of month for all X-students

New topics in Big data & Industrial Case studies will be covered. All the enrolled students of Hadoop plus will get an Access to Hadoop trends for a year. Additionally , 4 classroom workshops will be held in a year in 5 cities to cover important topics Cities for workshop- Mumbai, Pune, Banglore, Kolkata and Delhi only

testimonials

We sincerely appreciate the flexibility of teaching and customized guidance that the institute provided each of us. The intensity and rigour of the programme prepares one for high pressure situations. We are very grateful for the very valuable training and assistance provided to us by EDUPRISTINE.

I appreciate largely to the content part which covers practical aspects of modeling which we used on day to day base. We worked on R software expressively. We also touch on SPSS, Ms- Excel software. Edupristine done great job in combing the entire course..

Disclaimer

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